- How I Became a Data Scientist
The Sunday before last was my fabulous final shift, as a food server, on the historic sidewalks of San Francisco’s Castro District. My “part-time” adventure in the service industry took off in Vegas (double-fabulous) where I attended college, and it ignited an earnest appreciation for relating to strangers.
I graduated with an MS in Physics in August 2019, a week after I was hired at Harvey’s Restaurant. After spending 18-months performing research as a PhD candidate in an isolated concrete bunker, affectionately known as “the cave,” I was seeking community in vocation. I was furloughed in March 2020 due to COVID-19 and discovered my enthusiasm for Data Science by early May. I attended webinars on computer vision and artificial intelligence, and took advantage of private conferences offering open webinars with free registration due to the global pandemic. After six months of clinching my pennies and exploring online courses in Python, I enrolled in General Assembly’s three-month Data Science Immersive program.
I originally came to the Bay Area in May 2018 on a one year fellowship to perform research at Berkeley Lab (LBNL). The research award from the Department of Energy Office of Science was an exciting experience because we were making movies of molecules in their native frame (sub-angstrom, femtosecond). The beamline was made of electrons, and we imaged diffraction rings by highly sensitive cameras as the target molecule interacted with the charged pulse. I’ve performed an integral role in molecular imaging experiments at national laboratories and large multi-user facilities all over the world. From Paris and Berlin, to New York and Denver, I have had the opportunity to work with leading experts from a diverse spectrum of cultures and professional backgrounds. I am a deep thinker with a love for the collaborative nature of problem solving.
Specifically, my research experience has instilled in me an interest in challenges related to scene recognition and automation. The quantitative and analytic nature of physics excites me and I hope to pursue machine learning solutions to challenging business problems in the same way. Most of all, I aspire to collaborate with others on data driven tasks in ways that leverage my experience in the service industry with my background in mathematics to make a meaningful impact on my community here and now.
Check out my online portfolio showcasing a few favorite projects and connect with me on LinkedIn!
